8 citations · 10 across the 4 of their papers we have counts for
4 papers
Implementing Deep Reinforcement Learning-Based Grid Voltage Control in Real-World Power Systems: Challenges and Insights
Di Shi, Qiang Zhang, Mingguo Hong +4
Deep reinforcement learning (DRL) holds significant promise for managing voltage control challenges in simulated power grid environments. However, its real-world application in pow…
Cloud Deployment of Large-Scale Electromagnetic Transient Simulation -- Discovery and Experiences
Xiaochuan Luo, Jason Ploof, Xinghao Fang +2
Electromagnetic Transient (EMT) simulation starts to play a critical role in modern power system planning and operations due to large penetration of inverter based resources (IBRs)…
Physics-Aware Neural Dynamic Equivalence of Power Systems
Qing Shen, Yifan Zhou, Qiang Zhang +3
This letter devises Neural Dynamic Equivalence (NeuDyE), which explores physics-aware machine learning and neural-ordinary-differential-equations (ODE-Net) to discover a dynamic eq…
Scalable Neural Dynamic Equivalence for Power Systems
Qing Shen, Yifan Zhou, Huanfeng Zhao +4
Traditional grid analytics are model-based, relying strongly on accurate models of power systems, especially the dynamic models of generators, controllers, loads and other dynamic…